Search: “inference”

Increasing active parameters per token in MOE (Qwen 35B A4B+) reduce reasoning token by 8.5% - and you don't need to train or finetune!

model-releasesr-localllama

I want to share a short paper just published exploring a simple but surprisingly effective optimization for sparse MoE reasoning models. The idea: Instead of retraining anything, we just tweak the rou

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Research

InstEditSeg: Instruction-Driven Image Editing for Polyp and Skin Lesion Segmentation

DGX agent

arXiv:2609.02004v1 Announce Type: cross Abstract: Accurate segmentation of polyps and skin lesions is pivotal for clinical diagnosis, yet existing methods struggle with low contrast, ambiguous boundar

researcharxiv-cs-ai

3 Sept 2026

Local Ai

Integrated Laser Scanning and Image-Based Topology Optimization Techniques for Detection and Quantification of Visible and Subsurface Structural Defects

arXiv:2609.01808v1 Announce Type: new Abstract: Reliable characterization of structural defects requires methods capable of resolving both directly observable surface damage and damage that is not vis

local-aiarxiv-cs-cv

Learning the Constitutive Behavior of Materials via Neural Operators and Causal Attention: Case Studies in Plasticity and Damage

arXiv:2609.02194v1 Announce Type: new Abstract: Classical constitutive modeling of path-dependent inelastic materials relies on internal state variables whose evolution equations must be postulated ba

Linear Fusion MultiDiffusion for Fast Training-Free Spherical Panorama Generation

arXiv:2609.01997v1 Announce Type: new Abstract: We propose LF-MultiDiffusion, a training-free panorama generation method that extends MultiDiffusion to support linear projections between target and re

safetyarxiv-cs-cv

LoFi RADIO: A Distilled In-Domain Backbone Applied for Artifact-Severity Grading of Ultra-Low-Field Neonatal Brain MR

arXiv:2609.02676v1 Announce Type: cross Abstract: Ultra-low-field MRI makes neonatal brain imaging deploy- able in low-resource settings, but its low SNR, lack of shielding, and long scan duration mak

applicationsarxiv-cs-cv

LoRA-TSD: Tangent-Space Spectral Descent for LoRA via Muon-Style Updates

arXiv:2609.02734v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) is the standard way to fine-tune large models, yet when its two factors are trained independently, the update ignores the geo

Hardware

MultiGraspNet: A Multitask 3D Vision Model for Multi-gripper Robotic Grasping

arXiv:2602.06504v2 Announce Type: replace-cross Abstract: Vision-based models for robotic grasping automate critical, repetitive, and draining industrial tasks. Existing approaches are typically limit

hardwarearxiv-cs-cv

Network-Aware Forecasting on Wireless Access Points

arXiv:2609.01957v1 Announce Type: cross Abstract: Enterprise wireless access points (APs) are promising platforms for predictive machine learning (ML), but their primary responsibility remains providi

applicationsarxiv-cs-lg

NS-VLA: Towards Neuro-Symbolic Vision-Language-Action Models

arXiv:2603.09542v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are formulated to ground instructions in visual context and generate action sequences for robotic manipulation.

safetyarxiv-cs-ro

Ollama Pro is 20, but the new '60 credits' are more like $7-8 elsewhere

Everyone is talking about how the new credit system gives significantly less usage than the old Ollama Pro limits, but there's another part of the pricing that seems a bit crazy to me. For example, I

model-releasesr-ollama

Industry

OpenAI calls GPT-6 Astra the 'world's best computer use model'; in tests, it booked DMV appointments and searched job listings faster than the average person (Maxwell Zeff/Wired)

Maxwell Zeff / Wired: OpenAI calls GPT-6 Astra the “world's best computer use model”; in tests, it booked DMV appointments and searched job listings faster than the average person — OpenAI leaders thi

industrytechmeme

PaperCompiler: Faithful Paper-to-Code Generation via Repository-Level Specification Compilation

arXiv:2609.02272v1 Announce Type: cross Abstract: Faithfully translating research papers into repository-level implementations remains challenging because papers often describe methods at a high level

Tutorials

Physics-Driven Independent Pair Generation for Iterative Self-Supervised Low-Dose CT Denoising

arXiv:2609.02654v1 Announce Type: new Abstract: Low-dose computed tomography (LDCT) measurements contain mixed Poisson-Gaussian noise. However, most self-supervised methods rely on generic image stati

tutorialsarxiv-cs-cv

Post-Training Ternarization of Qwen3-4B Capability, Effective Bit Budget, Storage Compression, and Deployment

arXiv:2609.01962v1 Announce Type: new Abstract: Ultra-low-bit language models can reduce storage and memory bandwidth, but a nominal '1.58-bit' label does not fully describe the stored representation,

Privacy Washing: Detecting Internal Contradictions in Privacy Policies

arXiv:2609.02055v1 Announce Type: cross Abstract: Privacy policies may contain internal contradictions in which commitments are undermined by practices documented elsewhere in the same policy. We oper

safetyarxiv-cs-cl

Probing Cultural Signals in Large Language Models through Author Profiling

model-releasesarxiv-cs-cl

arXiv:2603.16749v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in applications with societal impact, raising concerns about the cultural biases they encode.

Quantum MeanFlow: single-shot generative sampling on NISQ hardware

arXiv:2609.02186v1 Announce Type: cross Abstract: Quantum generative models offer a promising framework for exploring whether quantum computation can enhance generative machine learning. Flow matching

Local Ai

RAFT-DVC: Resolution-Aware Machine Learning-Based Digital Volume Correlation

arXiv:2609.01876v1 Announce Type: new Abstract: Digital volume correlation (DVC) provides three-dimensional full-field displacement measurements from volumetric images, but how the internal resolution

local-aiarxiv-cs-cv

Rendering-in-the-Loop: An Execution-Driven Agent for Interactive Web Development

model-releasesarxiv-cs-cv

arXiv:2609.02088v1 Announce Type: new Abstract: Multimodal large language models have achieved remarkable progress in front-end web development, generating interactive webpages from multimodal referen

Retrosynthesis of Synthetic Media for Explainable AI Provenance Forensics

arXiv:2609.02268v1 Announce Type: cross Abstract: With the rapid proliferation of generative models on Machine Learning as a Service (MLaaS) platforms, reliably tracing the provenance of synthetic med

Reviewing the Reviewer: LLM-Assisted Reviewer Feedback Generation for Guideline Compliance

arXiv:2602.10118v2 Announce Type: replace Abstract: Peer review is central to scientific quality, yet reliance on simple heuristics, namely lazy thinking and non-specific critiques, has threatened rev

researcharxiv-cs-cl

Agents

RideSkill: A Hierarchical Algorithm for Generalized Ride Sharing with LLM-Driven Automatic Evolution

arXiv:2609.02250v1 Announce Type: cross Abstract: Ride-sharing, which allows multiple passengers with different origin-destination (OD) pairs to share a single vehicle, is a challenging operational pr

agentsarxiv-cs-cl

RVSD: Retrieval Vision Sparse Decoding for Mitigating Visual Hallucinations in Large Vision-Language Models

arXiv:2609.02731v1 Announce Type: cross Abstract: Large vision-language models have achieved remarkable success in vision-language tasks. However, they remain prone to Visual Hallucinations (VHs), und

applicationsarxiv-cs-ai

Scalable Bayesian Optimization of Composite Functions for Image-Based Inverse Problems in Materials Characterization

arXiv:2609.02126v1 Announce Type: new Abstract: Estimating physical parameters from scientific images is a common inverse problem in materials characterization that often relies on expensive physics-b

Secure AI-Driven Super-Resolution for Real-Time Mixed Reality Applications

arXiv:2512.15823v3 Announce Type: replace-cross Abstract: Immersive formats such as 360{eg} and 6DoF point cloud videos require high bandwidth and low latency, posing challenges for real-time AR/VR st

Signal or Noise? Auditing Rotation-Induced Saliency Drift in Medical and Aerial Imaging

arXiv:2609.02224v1 Announce Type: cross Abstract: Post-hoc saliency maps such as Grad-CAM are increasingly used to audit why a deployed vision model made a decision, yet the heatmap drifts when the in

safetyarxiv-cs-ai

Tutorials

SlowFast-SCI: Slow-Fast Deep Unfolding Learning for Spectral Compressive Imaging

arXiv:2509.16509v3 Announce Type: replace Abstract: Humans learn in two complementary ways: a slow, cumulative process that builds broad, general knowledge, and a fast, on-the-fly process that capture

tutorialsarxiv-cs-cv

Structured-Prior-Guided Diffusion Inpainting with Physical Consistency for Traffic Sign Augmentation

arXiv:2609.02348v1 Announce Type: new Abstract: Traffic sign detection faces a long-tailed data distribution. Many rare signs matter as much as common ones from a regulatory standpoint, yet they have

researcharxiv-cs-cv

text2ql: Multi-Target Natural Language Querying via a Language-Agnostic Intermediate Representation

arXiv:2609.02115v1 Announce Type: cross Abstract: Natural language interfaces to databases have traditionally suffered from three structural limitations: exclusive targeting of relational SQL, uncondi

Thinking effort aligns between humans and reasoning models in abductive reasoning

arXiv:2609.01867v1 Announce Type: cross Abstract: A major question in cognitive modeling concerns the behavioral alignment between large language models and humans across linguistic and non-linguistic

safetyarxiv-cs-ai

Thinking in Pictures: A Systematic Benchmark for Reasoning-driven Image Generation

model-releasesarxiv-cs-cv

arXiv:2609.02864v1 Announce Type: new Abstract: Recent advancements in unified generative models (UGMs) and world simulators have achieved unprecedented results in visual perception and synthesis. How

Toward Robust LiDAR Semantic Segmentation for Real-World Deployment: Evaluation under Coarse Labels, Adverse Conditions, and Domain Shifts

model-releasesarxiv-cs-ro

arXiv:2609.02830v1 Announce Type: new Abstract: LiDAR-based semantic segmentation is a core perception module for autonomous vehicles and mobile robots. Despite the strong performance of recent state-

Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codes

arXiv:2510.06257v2 Announce Type: replace-cross Abstract: Quantum error correction (QEC) is essential for scalable quantum computing, yet decoding errors via conventional algorithms result in limited

Towards One-for-All Robustness Across a Continuum of Threat Levels

arXiv:2609.02440v1 Announce Type: cross Abstract: Adversarially robust models often overfit to a specific attack budget, necessitating multiple specialized models for diverse and dynamic adversarial e

Tri-Band Channel Measurement-Enabled Multi-Layer Digital Twin for Terahertz Wireless Data Centers

arXiv:2609.01699v1 Announce Type: new Abstract: The rapid growth of AI computing has driven increasing demands for flexible and high-capacity data-center interconnections. Owing to its ultra-wide band

VakyArth: Evaluating Pragmatic Competence in LLMs across Indic Languages

arXiv:2609.01788v1 Announce Type: cross Abstract: Real-world communication often requires pragmatic reasoning: interpreting meanings implied through context and cultural convention rather than stated

When Can Large Reasoning Models Save Thinking? Mechanistic Analysis of Behavioral Divergence in Reasoning

arXiv:2505.15276v2 Announce Type: replace Abstract: Large reasoning models (LRMs) have achieved remarkable success on complex tasks, yet their tendency to 'overthink' leads to inefficiencies. Although

Agents

When Evidence Shapes Collaboration: Knowledge-Conditioned Topology Generation for Multi-Agent Systems

arXiv:2608.27984v2 Announce Type: replace Abstract: Multi-Agent Systems (MAS) have recently moved from static workflows toward dynamically generated collaboration topologies. However, existing topolog

agentsarxiv-cs-ai

XMerge: Cross-Axis Selection and Reconstructive Layer Merging for LLM Depth Compression

model-releasesarxiv-cs-cl

arXiv:2609.02083v1 Announce Type: cross Abstract: Removing complete transformer layers preserves a standard serving architecture, but existing depth-compression methods can lose substantial quality, a

A Closed-Loop Evaluation of Capability Loss and Recovery in Compressed Driving Policies

arXiv:2609.00718v1 Announce Type: new Abstract: Many automobile and mobility companies deploy learned driving policies on embedded computers with limited memory and power. Pruning, knowledge distillat

safetyarxiv-cs-ai

A Mathematical Theory of Reusable Neural Bases for Network Compression

arXiv:2609.01550v1 Announce Type: cross Abstract: As large AI models become increasingly prevalent across a wide range of applications, memory cost has become a critical bottleneck in both training an

Accelerating Chemical Kinetics for Exoplanet Atmospheres using Neural Networks

arXiv:2609.00428v1 Announce Type: cross Abstract: Observations increasingly reveal the coupled radiative, chemical, and dynamical processes that shape exoplanet atmospheres. Interpreting these atmosph

AnalysisBank: An Expert Analysis Pattern Library for Financial Report Generation

arXiv:2609.00818v1 Announce Type: new Abstract: We argue that financial report generation should operate at the analytical rather than structural level, composing content from data-derived insights ra

applicationsarxiv-cs-ai

ASSERT: Adaptive Stochastic Sampling for Robust Diffusion Models on Analog Compute-in-Memory Hardware

arXiv:2609.00955v1 Announce Type: new Abstract: Diffusion models achieve strong image generation quality but incur high iterative denoising costs. Analog compute-in-memory (CIM) can accelerate matrix-

safetyarxiv-cs-cv

AutoConcept: Training-Free Concept-Guided Reranking for Metadata-Available Composed Image Retrieval

arXiv:2609.01456v1 Announce Type: cross Abstract: Composed image retrieval (CIR) retrieves a target image from a reference image and a text modification. This paper studies metadata-available CIR rera

safetyarxiv-cs-cl

Beyond Blind Compliance: Benchmarking Task Verification in OCR Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.00232v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved strong performance on OCR-centric document understanding and text-rich visual reasoning benchmark

Beyond Language Priors: Diagnosing and Fixing Visual-Origin Hallucinations in Multimodal LLM

arXiv:2609.00231v1 Announce Type: new Abstract: Existing research on object hallucination in multimodal large language models (MLLMs) predominantly attributes the problem to language priors such as ov

researcharxiv-cs-cv